94 research outputs found
Low-Power Reconfigurable Architectures for High-Performance Mobile Nodes
Modern embedded systems have an emerging demand on high
performance and low power circuits. Traditionally special functional units for
each application are developed separately. These are plugged to a general
purpose processors to extend its instruction set making it an application specific
instruction set processor. As this strategy reaches its boundaries in area and
complexity reconfigurable architectures propose to be more flexible. Thus
combining both approaches to a reconfigurable application specific processor is
going to be the upcoming solution for future embedded systems
Cost-Efficient Soft-Error Resiliency for ASIP-based Embedded Systems
Recent decades have witnessed the rapid growth of embedded systems. At present, embedded systems are widely applied in a broad range of critical applications including automotive electronics, telecommunication, healthcare, industrial electronics, consumer electronics military and aerospace. Human society will continue to be greatly transformed by the pervasive deployment of embedded systems. Consequently, substantial amount of efforts from both industry and academic communities have contributed to the research and development of embedded systems. Application-specific instruction-set processor (ASIP) is one of the key advances in embedded processor technology, and a crucial component in some embedded systems.
Soft errors have been directly observed since the 1970s. As devices scale, the exponential increase in the integration of computing systems occurs, which leads to correspondingly decrease in the reliability of computing systems. Today, major research forums state that soft errors are one of the major design technology challenges at and beyond the 22 nm technology node. Therefore, a large number of soft-error solutions, including error detection and recovery, have been proposed from differing perspectives. Nonetheless, most of the existing solutions are designed for general or high-performance systems which are different to embedded systems. For embedded systems, the soft-error solutions must be cost-efficient, which requires the tailoring of the processor architecture with respect to the feature of the target application.
This thesis embodies a series of explorations for cost-efficient soft-error solutions for ASIP-based embedded systems. In this exploration, five major solutions are proposed.
The first proposed solution realizes checkpoint recovery in ASIPs. By generating customized instructions, ASIP-implemented checkpoint recovery can perform at a finer granularity than what was previously possible. The fault-free performance overhead of this solution is only 1.45% on average. The recovery delay is only 62 cycles at the worst case. The area and leakage power overheads are 44.4% and 45.6% on average.
The second solution explores utilizing two primitive error recovery techniques jointly. This solution includes three application-specific optimization methodologies. This solution generates the optimized error-resilient ASIPs, based on the characteristics of primitive error recovery techniques, static reliability analysis and design constraints. The resultant ASIP can be configured to perform at runtime according to the optimized recovery scheme. This solution can strategically enhance cost-efficiency for error recovery.
In order to guarantee cost-efficiency in unpredictable runtime situations, the third solution explores runtime adaptation for error recovery. This solution aims to budget and adapt the error recovery operations, so as to spend the resources intelligently and to tolerate adverse influences of runtime variations. The resultant ASIP can make runtime decisions to determine the activation of spatial and temporal redundancies, according to the runtime situations. At the best case, this solution can achieve almost 50x reliability gain over the state of the art solutions.
Given the increasing demand for multi-core computing systems, the last two proposed solutions target error recovery in multi-core ASIPs. The first solution of these two explores ASIP-implemented fine-grained process migration. This solution is a key infrastructure, which allows cost-efficient task management, for realizing cost-efficient soft-error recovery in multi-core ASIPs. The average time cost is only 289 machine cycles to perform process migration. The last solution explores using dynamic and adaptive mapping to assign heterogeneous recovery operations to the tasks in the multi-core context. This solution allows each individual ASIP-based processing core to dynamically adapt its specific error recovery functionality according to the corresponding task's characteristics, in terms of soft error vulnerability and execution time deadline. This solution can significantly improve the reliability of the system by almost two times, with graceful constraint penalty, in comparison to the state-of-the-art counterparts
A Flexible Ultralight Hardware Security Module for EPC RFID Tags
Due to the rapid growth of using Internet of Things (IoT) devices in daily life, the need to achieve an acceptable level of security and privacy for these devices is rising. Security risks may include privacy threats like gaining sensitive information from a device, and authentication problems from counterfeit or cloned devices. It is more challenging to add security features to extremely constrained devices, such as passive Electronic Product Code (EPC) Radio Frequency Identification (RFID) tags, compared to devices that have more computational and storage capabilities.
EPC RFID tags are simple and low-cost electronic circuits that are commonly used in supply chains, retail stores, and other applications to identify physical objects. Most tags today are simple "license plates" that just identify the object they are attached to and have minimal security. Due to the security risks of new applications, there is an important need to implement secure RFID tags. Examples of the security risks for these applications include unauthorized physical tracking and inventorying of tags. The current commercial RFID tag designs use specialised hardware circuits approach. This approach can achieve the lowest area and power consumption; however, it lacks flexibility.
This thesis presents an optimized application-specific instruction set architecture (ISA) for an ultralight Hardware Security Module (HSM). HSMs are computing devices that protect cryptographic keys and operations for a device. The HSM combines all security-related functions for passive RFID tag. The goal of this research is to demonstrate that using an application-specific instruction set processor (ASIP) architecture for ultralight HSMs provides benefits in terms of trade-offs between flexibility, extensibility, and efficiency. Our novel application specific instruction-set architecture allows flexibility on many design levels and achieves acceptable security level for passive EPC RFID tag. Our solution moves a major design effort from hardware to software, which largely reduces the final unit cost.
Our ASIP processor can be implemented with 4,662 gate equivalent units (GEs) for 65 nm CMOS technology excluding cryptographic units and memories. We integrated and analysed four cryptographic modules: AES and Simeck block ciphers, WG-5 stream cipher, and ACE authenticated encryption module. Our HSM achieves very good efficiencies for both block and stream ciphers. Specifically for the AES cipher, we improve over a previous programmable AES implementation result by 32x. We increase performance dramatically and increase/decrease area by 17.97/17.14% respectively. These results fulfill the requirements of extremely constrained devices and allow the inclusion of cryptographic units into the datapath of our ASIP processor
A survey of secure middleware for the Internet of Things
The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area
A New Approximation Method for Constant Weight Coding and Its Hardware Implementation
In this chapter, a more memory-efficient method for encoding binary information into words of prescribed length and weight is presented. The solutions in existing work include complex float point arithmetic or extra memory overhead which make it demanding for resource-constrained computing platform. The solution we propose here solves the problems above yet achieves better coding efficiency. We also correct a crucial error in previous implementations of code-based cryptography by exploiting and tweaking the proposed encoder. For the time being, the design presented in this work is the most compact one for any code-based encryption schemes. We show, for instance, that our lightweight implementation of Niederreiter encrypting unit can encrypt approximately 1 million plaintexts per second on a Xilinx Virtex-6 FPGA, requiring 183 slices and 18 memory blocks
Hardware Implementation of Efficient Elliptic Curve Scalar Multiplication using Vedic Multiplier
This paper presents an area efficient and high-speed FPGA implementation of scalar multiplication using a Vedic multiplier. Scalar multiplication is the most important operation in Elliptic Curve Cryptography(ECC), which used for public key generation and the performance of ECC greatly depends on it. The scalar multiplication is multiplying integer k with scalar P to compute  Q=kP, where k is private key and P is a base point on the Elliptic curve. The Scalar multiplication underlying finite field arithmetic operation i.e. addition multiplication, squaring and inversion to compute Q. From these finite field operations, multiplication is the most time-consuming operation, occupy more device space and it dominates the speed of Scalar multiplication. This paper presents an efficient implementation of finite field multiplication using a Vedic multiplier.  The scalar multiplier is designed over Galois Binary field GF(2233) for field size=233-bit which is secured curve according to NIST. The performances of the proposed design are evaluated by comparing it with  Karatsuba based scalar multiplier for area and delay. The results show that the proposed scalar multiplication using Vedic multiplier has consumed 22% less area on FPGA and also has 12% less delay, than Karatsuba, based scalar multiplier. The scalar multiplier is coded in Verilog HDL, synthesize and simulated in Xilinx 13.2 ISE on Virtex6 FPGA
Public-Key Based Authentication Architecture for IoT Devices Using PUF
Nowadays, Internet of Things (IoT) is a trending topic in the computing
world. Notably, IoT devices have strict design requirements and are often
referred to as constrained devices. Therefore, security techniques and
primitives that are lightweight are more suitable for such devices, e.g.,
Static Random-Access Memory (SRAM) Physical Unclonable Functions (PUFs) and
Elliptic Curve Cryptography (ECC). SRAM PUF is an intrinsic security primitive
that is seeing widespread adoption in the IoT segment. ECC is a public-key
algorithm technique that has been gaining popularity among constrained IoT
devices. The popularity is due to using significantly smaller operands when
compared to other public-key techniques such as RSA (Rivest Shamir Adleman).
This paper shows the design, development, and evaluation of an
application-specific secure communication architecture based on SRAM PUF
technology and ECC for constrained IoT devices. More specifically, it
introduces an Elliptic Curve Diffie-Hellman (ECDH) public-key based
cryptographic protocol that utilizes PUF-derived keys as the root-of-trust for
silicon authentication. Also, it proposes a design of a modular hardware
architecture that supports the protocol. Finally, to analyze the practicality
as well as the feasibility of the proposed protocol, we demonstrate the
solution by prototyping and verifying a protocol variant on the commercial
Xilinx Zynq-7000 APSoC device
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Tradeoff Analysis for Combat Service Support Wireless Communications Alternatives
As the Army moves toward more mobile and agile forces and continued sustainment of numerous high-cost legacy logistics management systems, the requirement for wireless connectivity and a wireless network to supporting organizations has become ever more critical. There are currently several Army communications initiatives underway to resolve this wireless connectivity issue. However, to fully appreciate and understand the value of these initiatives, a Tradeoff Analysis is needed. The present study seeks to identify and assess solutions. The analysis identified issues that impede Interim Brigade Combat Team (IBCT) communication system integration and outlined core requirements for sharing of logistics data between the field and Army battle command systems. Then, the analysis examined wireless communication alternatives as possible solutions for IBCT logistics communications problems. The current baseline system was compared with possible alternatives involving tactical radio systems, wireless/near term digital radio, cellular satellite, and third-generation (3G) wireless technologies. Cellular satellite and 3G wireless technologies offer clear advantages and should be considered for later IBCTs
Energy analysis and optimisation techniques for automatically synthesised coprocessors
The primary outcome of this research project is the development of a methodology enabling fast automated early-stage power and energy analysis of configurable processors for system-on-chip platforms. Such capability is essential to the process of selecting energy efficient processors during design-space exploration, when potential savings are highest. This has been achieved by developing dynamic and static energy consumption models for the constituent blocks within the processors.
Several optimisations have been identified, specifically targeting the most significant blocks in terms of energy consumption. Instruction encoding mechanism reduces both the energy and area requirements of the instruction cache; modifications to the multiplier unit reduce energy consumption during inactive cycles. Both techniques are demonstrated to offer substantial energy savings.
The aforementioned techniques have undergone detailed evaluation and, based on the positive outcomes obtained, have been incorporated into Cascade, a system-on-chip coprocessor synthesis tool developed by Critical Blue, to provide automated analysis and optimisation of processor energy requirements. This thesis details the process of identifying and examining each method, along with the results obtained. Finally, a case study demonstrates the benefits of the developed functionality, from the perspective of someone using Cascade to automate the creation of an energy-efficient configurable processor for system-on-chip platforms
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